shrinkage {languageR} | R Documentation |
Simulated data set for illustrating shrinkage.
data(shrinkage)
A data frame with 200 observations on the following 6 variables.
intercept
frequency
subject
S1
,
S2
, ... , S10
.error
ranef
RT
## Not run: data(shrinkage) library(lme4, keep.source=FALSE) shrinkage.lmer = lmer(RT ~ frequency + (1|subject), data = shrinkage) shrinkage.lmList = lmList(RT ~ frequency | subject, data = shrinkage) # and visualize the difference between random regression # and mixed-effects regression mixed = coef(shrinkage.lmer)[[1]] random = coef(shrinkage.lmList) subj = unique(shrinkage[,c("subject", "ranef")]) subj = subj[order(subj$subject),] subj$random = random[,1] subj$mixed = mixed[,1] subj = subj[order(subj$random),] subj$rank = 1:nrow(subj) par(mfrow=c(1,2)) plot(subj$rank, subj$random, xlab="rank", ylab="RT", ylim=c(200,550), type="n") text(subj$rank, subj$random, as.character(subj$subject), cex=0.8, col="red") mtext("random regression", 3, 1) points(subj$rank, 400+subj$ranef, col="blue") abline(h=400) plot(subj$rank, subj$mixed, xlab="rank", ylab="RT", ylim=c(200,550), type="n") text(subj$rank, subj$mixed, as.character(subj$subject), cex=0.8, col = "red") mtext("mixed-effects regression", 3, 1) points(subj$rank, 400+subj$ranef, col="blue") abline(h=400) par(mfrow=c(1,1)) ## End(Not run)